pixi.toml

[project]
name = "nerfstudio"
description = "All-in-one repository for state-of-the-art NeRFs"
channels = ["nvidia/label/cuda-11.8.0", "nvidia", "conda-forge", "pytorch"]
platforms = ["linux-64"]

[system-requirements]
libc = { family="glibc", version="2.30" }

[tasks]
# || operator in pixi allows running a command after only if the command before || fails
tcnn-install = "python -c 'import tinycudann as tcnn' || python -m pip install ninja git+https://github.com/NVlabs/tiny-cuda-nn/#subdirectory=bindings/torch"
make-third_party-dir = {cmd="ls third_party || mkdir third_party"}
clone-hloc = {cmd="ls Hierarchical-Localization || git clone --recursive https://github.com/cvg/Hierarchical-Localization/", cwd = "third_party", depends_on=["make-third_party-dir"] }
hloc-install = {cmd="python -m pip install -e .", cwd = "third_party/Hierarchical-Localization" , depends_on=["clone-hloc"], outputs=["third_party/Hierarchical-Localization/hloc.egg-info/PKG-INFO"]}
post-install = {cmd="pwd", depends_on=["hloc-install", "tcnn-install"]}

download-dozer-data = {cmd="ls data/nerfstudio/dozer || ns-download-data nerfstudio --capture-name dozer"}
train-example-splat = {cmd="ns-train splatfacto --data data/nerfstudio/dozer/", depends_on=["post-install", "download-dozer-data"]}
train-example-nerf = {cmd="ns-train nerfacto --data data/nerfstudio/dozer/", depends_on=["post-install", "download-dozer-data"]}


[dependencies]
python = ">=3.8,<3.11"
pip = ">=24.0,<25"
cuda = {version = "*", channel="nvidia/label/cuda-11.8.0"}
pytorch-cuda = {version = "11.8.*", channel="pytorch"}
pytorch = {version = ">=2.2.0,<2.3", channel="pytorch"}
torchvision = {version = ">=0.17.0,<0.18", channel="pytorch"}
pyarrow = ">=15.0.2,<15.1"
colmap = ">=3.9.1,<3.10"


[pypi-dependencies]
nerfstudio = { path = ".", editable = true}